Step 02
Fine-tune your profile.
Your skill profile is the single most important thing on this site. Resume parsing gets you 70% of the way there. The last 30% is you setting the depth on each skill, your target role, a salary floor, and what you will not consider.
Skip it and every score is a guess. Spend ten minutes and you get sharper fit scores, less garbage in the dashboard, and a daily email that actually surfaces jobs worth opening.
The L1–L5 depth ladder
Each level is a step deeper, not a label switch.
Be honest about where you are. The engine matches you against what each job really needs, so inflated levels just produce false-positive scores you waste time on.
The engine reads each job description to figure out what depth the role actually needs, then compares it to your profile. That match or gap is the biggest single input to your fit score. Inflate your levels and the dashboard fills with jobs you cannot actually do.
Step 2
Your skills & preferences
28 skills · 5 categories
React / Next.js
TypeScript
Tailwind CSS
GraphQL
React Native
WebGL
Node.js
PostgreSQL
REST API design
Python
Go
Rust
AWS
Docker
CI/CD pipelines
Terraform
Kubernetes
Linux administration
SQL
Redis
BigQuery
dbt
Snowflake
Code review
Mentoring
Sprint planning
Hiring & interviewing
Cross-team comms
Target role
Sr. Engineer
Min salary
$140K
Work style
Remote
Locations
US only
Dealbreakers
Why this matters
Most job boards score postings against your resume text, so you get keyword matches. ShouldApply scores against your profile, which you actually maintain. Two engineers with the same resume can have very different profiles. One has four years in production React. The other shipped one project with it. Their fit scores for a senior frontend role should not be the same number, and with a real profile they aren't.
The five things you control
Skill depth (L1 to L5)
Rate each skill from L1 (familiar) to L5 (expert). The engine compares your depth to what each job actually demands. A role asking for L4 React when you have it at L2 will lose points fast. This is the moat over keyword matching.
Target role and seniority
Pick the title you want next. Drives filtering and the seniority alignment of your fit score.
Minimum salary
Set a floor. Jobs below it get flagged. Jobs that hide their range get scored on what we can infer.
Work style and locations
Remote, hybrid, or on-site, plus acceptable cities. Anything outside your range gets deprioritized.
Dealbreakers
Things that auto-disqualify a job: commission-only, contract, crypto, specific industries. Run before scoring.
What changes the moment you tune it
- Score quality. A 91 on a tuned profile means a callback. A 91 on a default one is a coin flip.
- Job pool quality. Dealbreakers and salary floors prune the noise before scoring.
- Why Not 100 reports. Real depths produce real gap reports. You learn what to fix, not what to guess at.
- Resume tailoring. The tailoring tool reads your depths to decide what to lead with.
- Daily match emails. Five jobs worth opening, not fifty worth ignoring.
Common mistakes when setting up a profile
Rating everything L4 or L5. If everything is expert, nothing is. Be ruthless. Most people have one or two L5s.
Skipping dealbreakers. Fastest cleanup tool you have. Five minutes usually cuts a third of the dashboard noise.
Vague target role. "Any engineering role" weights nothing. Pick the actual title you want next.
Salary floor too low. A floor below market just means more 60-scores. Set it to what you will actually accept.